Dozens of GPT-driven products are already on the market, and hundreds more are in development. These tools collectively aim to revolutionize traditional roles and processes, transforming them into dynamic, parallelized workflows using variants of LLM models, such as AutoGPT. Tools like GitHub Copilot, powered by OpenAI’s Codex, are demonstrating significant improvements in developer productivity, with some studies showing up to a 55% increase in task completion speed.
With the rapid adoption of genAI, robust change management and careful consideration of intellectual property protection are essential to ensure successful integration and safeguard sensitive data.
Emerj Senior Editor Matthew DeMello recently spoke with Craig Mackereth, EVP- Global Service Delivery, Rimini Street, on the ‘AI in Business’ podcast to discuss how IT teams in financial services are eager to experiment with generative AI (GenAI) and highlighted the importance of hands-on learning, change management, and cautious adoption due to the evolving nature of technology.
In the following analysis of their conversation, we examine two key insights
- Robust change management and IP protection: Developing and implementing strong change management strategies to support IT teams and protect intellectual property, ensuring successful AI integration while maintaining control over sensitive data.
- Centering AI initiatives around ROI: Prioritizing AI initiatives that promise a clear return on investment (ROI) within the first year. Commitment to measurable ROI builds confidence and support, fostering a strategic approach to AI implementation and ensuring financial viability from the outset.
Listen to the full episode below:
Guest: Craig Mackereth, Executive Vice President of Global Service Delivery, Rimini Street
Expertise: Customer service, System design, Project management
Brief Introduction: Craig Mackereth is the Executive Vice President for Global Service Delivery at Rimini Street. With a background spanning aerospace, defense, and financial services sectors, Craig brings extensive experience to his role at Rimini Street.
Robust Change Management and IP Protection
Craig opens up the podcast by identifying three key challenges that financial services teams face regarding the adoption and integration of generative AI:
- Uncertainty in Future Success: There’s a lot of investment and hype around gen AI, but it’s unclear which players or approaches will ultimately be successful. This uncertainty makes it difficult to decide where to invest, and choosing the wrong approach could be costly.
- Intellectual Property (IP) Leakage: Gen AI involves feeding models with content, often proprietary IP. There are concerns about how IP is used, controlled, and protected throughout the process. Organizations need to understand whether they retain control over their IP or if they are giving up some of it in exchange for broader capabilities.
- Change Management: Successfully implementing AI projects requires effective change management. It’s about more than just claiming to solve problems with AI; it is about understanding how AI will be integrated and how it will impact the organization. Ensuring that IT teams are brought along in this journey is crucial, as it prevents valuable team members from feeling left out or considering leaving if they feel their skills are becoming outdated or undervalued.
He goes on to emphasize the importance of strategic decision-making in AI implementation within digital transformation. Leaders need to differentiate, he says, between genuinely transformative AI initiatives and mere experimentation. They must consider if AI aligns with their brand’s values or poses risks due to its unpredictable nature.
“If you’re selecting when AI makes sense, as opposed to when it could potentially hurt the brand. That’s the sort of business decision that leaders need to be making here. And this is around it: ‘Am I really doing a digital transformation or am I just getting my hand in the water?’ is a very different thing.”
– Craig Mackereth, Executive Vice President of Global Service Delivery at Rimini Street
Craig, whose team has been using AI since 2019, underscores the need for caution in the conservative financial services industry, where trust is crucial. He advises leaders to ensure that AI enhances rather than undermines their brand’s reputation.
He then emphasizes that it will take a long time before a conservative or defensive approach to gen AI is possible. He sees value in a controlled, corporate use of such technology, especially when a brand’s reputation and sensitive data are at stake. However, he points out that the current technology libraries are fluid and constantly evolving, making it challenging to adopt a conservative stance.
Drawing on his experience in the aerospace, defense, and financial sectors, Craig underscores the importance of being cautious and responsible with sensitive information. Rapidly changing and untested technologies are not typically trusted or adopted for critical business operations in these industries.
Centering AI Initiatives Around ROI
He emphasizes the importance of corporate-level adoption of new technologies. He notes that real-world implementation and use are crucial for advancing each generation of technology. Craig highlights the potential for non-competitive collaboration in areas like consumer education on credit, cybersecurity, and philanthropic efforts, suggesting that such cooperation can be beneficial without threatening competitiveness.
Craig emphasizes that the first generation of AI should not be dismissed simply because it’s new. He suggests viewing it as a foundational building block for solving real-world business problems that offer a return on investment (ROI). He advises financial service leaders to start with AI projects that demonstrate clear value, as successful initial projects pave the way for further development and investment.
“If a project can’t pay for itself in the first year, and the project team that’s implementing is not willing to stand behind that commitment that it will return, whatever it costs in that first year, then you need to look a lot harder at that project. If they’re saying it’ll give an ROI, they’ll stand behind that ROI, and that ROI is going to be in the first 12 months, then lean in because that scenario where you can get your hands around it, it’s a building block. Stay caught up on first-generation or second-generation. You’re doing some AI work, you’re in the game, you’re on the field.”
–Craig Mackereth, Executive Vice President of Global Service Delivery at Rimini Street
In the end, he emphasizes the value of involving the IT team in AI projects, noting that they will naturally want to experiment and engage with the technology. He stresses the importance of change management, reminding leaders not to overlook the IT team’s enthusiasm for hands-on learning and experimentation.
Craig highlights that failure in initial projects shouldn’t be viewed negatively, as he says, “What’s the best way to learn something will break it, and then fix it.“ He asserts that AI’s unpredictable nature means not all outcomes can be foreseen, and initial setbacks can lead to significant successes in the future. The key is to use these experiences as learning opportunities rather than dismissing them outright.
